Extracting notional machines for databases

Daphne Miedema; Fenia Aivaloglou; Leonard Busuttil; Laura Farinetti; Martin Goodfellow; Giovanna Guerrini; Georgiana Haldeman; Yuhan Pan; Sujeeth Goud Ramagoni; Chandrika Satyavolu; Raja Sooriamurthi; Xiaoying Tu; Liviana Tudor

doi:10.1145/3724389.3731277

Extracting notional machines for databases

Daphne Miedema, Fenia Aivaloglou, Leonard Busuttil, Laura Farinetti, Martin Goodfellow, Giovanna Guerrini, Georgiana Haldeman, Yuhan Pan, Sujeeth Goud Ramagoni, Chandrika Satyavolu, Raja Sooriamurthi, Xiaoying Tu, Liviana Tudor

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

Abstract

Database education is a cornerstone under many of the more popular topics in computer science such as machine learning and visualization. Although, in recent years, more fundamental research into database education has come out, there are many more ways in which it can be extended. Research on the practice of teaching databases, namely on the educational materials and explanations of teachers, can help us create new building blocks for fundamental research. This working group aims to collect and present notional machines of different types, for a wide range of database subtopics. These materials offer and updated context for database educators to design their courses from, as well as open up pathways of further research into database education.

Original language	English
Title of host publication	ITiCSE 2025 - Proceedings of the 2025 Conference on Innovation and Technology in Computer Science Education
Place of Publication	New York, NY
Pages	693-694
Number of pages	2
ISBN (Electronic)	9798400715693
DOIs	https://doi.org/10.1145/3724389.3731277
Publication status	Published - 17 Jun 2025

Keywords

database education
teaching
subtopics

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10.1145/3724389.3731277

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Miedema, D., Aivaloglou, F., Busuttil, L., Farinetti, L., Goodfellow, M., Guerrini, G., Haldeman, G., Pan, Y., Ramagoni, S. G., Satyavolu, C., Sooriamurthi, R., Tu, X., & Tudor, L. (2025). Extracting notional machines for databases. In ITiCSE 2025 - Proceedings of the 2025 Conference on Innovation and Technology in Computer Science Education (pp. 693-694). https://doi.org/10.1145/3724389.3731277

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year = "2025",

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Miedema, D, Aivaloglou, F, Busuttil, L, Farinetti, L, Goodfellow, M, Guerrini, G, Haldeman, G, Pan, Y, Ramagoni, SG, Satyavolu, C, Sooriamurthi, R, Tu, X & Tudor, L 2025, Extracting notional machines for databases. in ITiCSE 2025 - Proceedings of the 2025 Conference on Innovation and Technology in Computer Science Education. New York, NY, pp. 693-694. https://doi.org/10.1145/3724389.3731277

TY - GEN

T1 - Extracting notional machines for databases

AU - Miedema, Daphne

AU - Aivaloglou, Fenia

AU - Busuttil, Leonard

AU - Farinetti, Laura

AU - Goodfellow, Martin

AU - Guerrini, Giovanna

AU - Haldeman, Georgiana

AU - Pan, Yuhan

AU - Ramagoni, Sujeeth Goud

AU - Satyavolu, Chandrika

AU - Sooriamurthi, Raja

AU - Tu, Xiaoying

AU - Tudor, Liviana

PY - 2025/6/17

Y1 - 2025/6/17

N2 - Database education is a cornerstone under many of the more popular topics in computer science such as machine learning and visualization. Although, in recent years, more fundamental research into database education has come out, there are many more ways in which it can be extended. Research on the practice of teaching databases, namely on the educational materials and explanations of teachers, can help us create new building blocks for fundamental research. This working group aims to collect and present notional machines of different types, for a wide range of database subtopics. These materials offer and updated context for database educators to design their courses from, as well as open up pathways of further research into database education.

AB - Database education is a cornerstone under many of the more popular topics in computer science such as machine learning and visualization. Although, in recent years, more fundamental research into database education has come out, there are many more ways in which it can be extended. Research on the practice of teaching databases, namely on the educational materials and explanations of teachers, can help us create new building blocks for fundamental research. This working group aims to collect and present notional machines of different types, for a wide range of database subtopics. These materials offer and updated context for database educators to design their courses from, as well as open up pathways of further research into database education.

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KW - teaching

KW - subtopics

U2 - 10.1145/3724389.3731277

DO - 10.1145/3724389.3731277

M3 - Conference contribution book

SP - 693

EP - 694

BT - ITiCSE 2025 - Proceedings of the 2025 Conference on Innovation and Technology in Computer Science Education

CY - New York, NY

ER -

Extracting notional machines for databases

Abstract

Keywords

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